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Prognostic survival model for people diagnosed with invasive cutaneous melanoma

Overview of attention for article published in BMC Cancer, January 2015
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Mentioned by

twitter
1 tweeter
facebook
1 Facebook page

Citations

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19 Dimensions

Readers on

mendeley
33 Mendeley
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1 CiteULike
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Title
Prognostic survival model for people diagnosed with invasive cutaneous melanoma
Published in
BMC Cancer, January 2015
DOI 10.1186/s12885-015-1024-4
Pubmed ID
Authors

Peter D Baade, Patrick Royston, Philipa H Youl, Martin A Weinstock, Alan Geller, Joanne F Aitken

Abstract

BackgroundThe ability of medical practitioners to communicate risk estimates effectively to patients diagnosed with melanoma relies on accurate information about prognostic factors and their impact on survival. This study reports the development of one of the few melanoma prognostic models, called the Melanoma Severity Index (MSI), based on population-based cancer registry data.MethodsData from the Queensland Cancer Registry for people (20¿89 years) diagnosed with a single invasive melanoma between 1995 and 2008 (n¿=¿28,654; 1,700 melanoma deaths). Additional clinical information about metastasis, ulceration and positive lymph nodes was manually extracted from pathology forms. Flexible parametric survival models were combined with multivariable fractional polynomial for selecting variables and transformations of continuous variables. Multiple imputation was used for missing covariate values.ResultsThe MSI contained the variables thickness (transformed, explained 40.6% of variation in survival), body site (additional 1.9% in variation), metastasis (1.8%), positive nodes (0.7%), ulceration (1.3%), age (1.1%). Royston and Sauerbrei¿s D statistic (measure of discrimination) was 1.50 (95% CI¿=¿1.44, 1.56) and the corresponding RD2 (measure of explained variation) was 0.47 (0.45, 0.49), demonstrating strong explanatory performance. The Harrell-C statistic was 0.88 (0.88, 0.89). Lacking an external validation dataset, we applied internal-external cross validation to demonstrate the consistency of the prognostic information across geographically-defined subsets of the cohort.ConclusionsThe MSI provides good ability to predict survival for melanoma patients. Beyond the immediate clinical use, the MSI may have important public health and research applications for evaluations of public health interventions aimed at reducing deaths from melanoma.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
Unknown 32 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 15%
Other 4 12%
Researcher 4 12%
Student > Ph. D. Student 4 12%
Student > Bachelor 3 9%
Other 8 24%
Unknown 5 15%
Readers by discipline Count As %
Medicine and Dentistry 14 42%
Agricultural and Biological Sciences 5 15%
Biochemistry, Genetics and Molecular Biology 3 9%
Mathematics 1 3%
Psychology 1 3%
Other 1 3%
Unknown 8 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 January 2016.
All research outputs
#7,458,967
of 12,372,945 outputs
Outputs from BMC Cancer
#1,978
of 4,558 outputs
Outputs of similar age
#127,717
of 265,047 outputs
Outputs of similar age from BMC Cancer
#5
of 13 outputs
Altmetric has tracked 12,372,945 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,558 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 51% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,047 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.